751–760 of 1001 posts
Maybe you are, but I didn't get a Master's degree to produce quick shit for shareholders
> Does an intern cost $20/month? Because that’s what Cursor.ai costs.
> Part of being a senior developer is making less-able coders productive, be they fleshly or algebraic.
But do you know what another part of being a senior developer is? Not just making them more productive, but also guiding the junior developers into becoming better, independent, self-tasking, senior coders. And that feedback loop doesn't exist here.
We're robbing ourselves of good future developers, because we aren't even thinking about the fact that the junior devs are actively learning from the small tasks we give them.
Will AI completely replace devs before we all retire? Maybe. Maybe not.
But long before that, the future coders who aren't being hired and trained because a senior dev doesn't understand that the junior devs become senior devs (and that's an important pipeline) and would rather pay $20/month for an LLM, are going to become a major loss/ brain drain domestically.
Who are these friends? Are they in the room with us right now? Look, maybe my experience is atypical but I’m an AI skeptic and I know plenty of others. I’ve never heard people claim that LLMs are a fad or going to go away. I’ve seen lots of people: * think that conflating LLMs and “AI” produces a lot of poorly reasoned arguments * doubt the economic narratives being built around LLM technology * think the current rat…
Case in point: WWW and the “dot com” bubble. Dot com was a bubble, but the WWW (and Internet) was a big thing that transformed all major societies. It survived the bust that followed after the boom.
Are LLMs here to stay? We can guess, but as usual, time will tell.
The argument that I've heard against LLMs for code is that they create bugs that, by design, are very difficult to spot. The LLM has one job, to make code that looks plausible. That's it. There's no logic gone into writing that bit of code. So the bugs often won't be like those a programmer makes. Instead, they can introduce a whole new class of bug that's way harder to debug.
What makes you say that? If LLMs didn't reason about things, they wouldn't be able to do one hundredth of what they do.
When I ask chatGTP to generate the code for a M4F MCU that implements the VirtIO code for accessing the GPIO through RPMSG using FreeRTOS it produces two answers that are both incomplete and incorrect.
Giving it only 1 or 2 complex requirements at a time, and then having it iterate, I've found to be more effective.
Most LLMs don't "think", so when asking an LLM something, I generally try to think "would I be able to do this without thinking, if I had all the knowledge, but just had to start typing and go?".
You could break down your prompt into separate prompts like this maybe: https://chatgpt.com/share/683eb7d7-e7ec-8012-8b3b-e34d523dc9...
I think it broke things down in a weird way, but I definitely can't analyse the correctness of anything it outputs in this domain :P
Coding specific agents like Copilot might be better able to handle a complex initial prompt, since they take the initial prompt, and use LLMs to break it down into smaller steps, which ChatGPT doesn't do. They can sort of "think". Deep research AIs also have a sort of thinking too, so might do better.
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I'm a bit on the fence myself, as I think it's very harmful, but I can also see ways it can be useful. But it's absolutely mindblowing how this is nearly always completely out of the discussion even though our current way of living and powering things is on a timer and we still haven't addressed it as a whole.
In no way can AI be used for anything larger than generating singular functions or anything that would require writing to or modifying multiple files.
Technically you might be able to pull off having AI change multiple files for you in one go, but you'll quickly run into sort of "Adobe Dreamviewer" type of issue where your codebase is dominated by generated code which only the AI that generated it is able to properly extend and modify.
I remember when Dreamviewer was a thing, but you essentialyl had to make a choice between sticking with it forever for the project or not using it at all, because it would basically convert your source code into it's own proprietary format due to it becoming so horribly messy and unreadable.
Regardless, AI is absolutely incredible and speeds up development by a great deal, (even) if you only use it to generate small snippets at the time.
AI is also an absolute godsend for formatting and converting stuff from anything and to anything - you could e.g. dump your whole database structure to Gemini and ask it to generate an API against it; big task, but since it is basically just a conversion task, it will work very well.
One thing that I find truly amazing is just the simple fact that you can now be fuzzy with the input you give a computer, and get something meaningful in return. Like, as someone who grew up learning to code in the 90s it always seemed like science fiction that we'd get to a point where you could give a computer some vague human level instructions and get it more or less do what you want.
I think this article is pretty spot on — it articulates something I’ve come to appreciate about LLM-assisted coding over the past few months. I started out very sceptical. When Claude Code landed, I got completely seduced — borderline addicted, slot machine-style — by what initially felt like a superpower. Then I actually read the code. It was shockingly bad. I swung back hard to my earlier scepticism, probably even…
One thing that really bothered me that the author glossed over (perhaps they don't care, given the tone of the article) is where they said: > Does an intern cost $20/month? Because that’s what Cursor.ai costs. > Part of being a senior developer is making less-able coders productive, be they fleshly or algebraic. But do you know what another part of being a senior developer is? Not just making them more productive, bu…